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Modeling Nosocomial Infections of Methicillin-Resistant Staphylococcus aureus with Environment Contamination(*)
In this work, we investigate the role of environmental contamination on the clinical epidemiology of antibiotic-resistant bacteria in hospitals. Methicillin-resistant Staphylococcus aureus (MRSA) is a bacterium that causes infections in different parts of the body. It is tougher to treat than most s...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5428062/ https://www.ncbi.nlm.nih.gov/pubmed/28373644 http://dx.doi.org/10.1038/s41598-017-00261-1 |
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author | Wang, Lei Ruan, Shigui |
author_facet | Wang, Lei Ruan, Shigui |
author_sort | Wang, Lei |
collection | PubMed |
description | In this work, we investigate the role of environmental contamination on the clinical epidemiology of antibiotic-resistant bacteria in hospitals. Methicillin-resistant Staphylococcus aureus (MRSA) is a bacterium that causes infections in different parts of the body. It is tougher to treat than most strains of Staphylococcus aureus or staph, because it is resistant to some commonly used antibiotics. Both deterministic and stochastic models are constructed to describe the transmission characteristics of MRSA in hospital setting. The deterministic epidemic model includes five compartments: colonized and uncolonized patients, contaminated and uncontaminated health care workers (HCWs), and bacterial load in environment. The basic reproduction number R (0) is calculated, and its numerical and sensitivity analysis has been performed to study the asymptotic behavior of the model, and to help identify factors responsible for observed patterns of infections. A stochastic epidemic model with stochastic simulations is also presented to supply a comprehensive analysis of its behavior. Data collected from Beijing Tongren Hospital will be used in the numerical simulations of our model. The results can be used to provide theoretical guidance for designing efficient control measures, such as increasing the hand hygiene compliance of HCWs and disinfection rate of environment, and decreasing the transmission rate between environment and patients and HCWs. |
format | Online Article Text |
id | pubmed-5428062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54280622017-05-15 Modeling Nosocomial Infections of Methicillin-Resistant Staphylococcus aureus with Environment Contamination(*) Wang, Lei Ruan, Shigui Sci Rep Article In this work, we investigate the role of environmental contamination on the clinical epidemiology of antibiotic-resistant bacteria in hospitals. Methicillin-resistant Staphylococcus aureus (MRSA) is a bacterium that causes infections in different parts of the body. It is tougher to treat than most strains of Staphylococcus aureus or staph, because it is resistant to some commonly used antibiotics. Both deterministic and stochastic models are constructed to describe the transmission characteristics of MRSA in hospital setting. The deterministic epidemic model includes five compartments: colonized and uncolonized patients, contaminated and uncontaminated health care workers (HCWs), and bacterial load in environment. The basic reproduction number R (0) is calculated, and its numerical and sensitivity analysis has been performed to study the asymptotic behavior of the model, and to help identify factors responsible for observed patterns of infections. A stochastic epidemic model with stochastic simulations is also presented to supply a comprehensive analysis of its behavior. Data collected from Beijing Tongren Hospital will be used in the numerical simulations of our model. The results can be used to provide theoretical guidance for designing efficient control measures, such as increasing the hand hygiene compliance of HCWs and disinfection rate of environment, and decreasing the transmission rate between environment and patients and HCWs. Nature Publishing Group UK 2017-04-03 /pmc/articles/PMC5428062/ /pubmed/28373644 http://dx.doi.org/10.1038/s41598-017-00261-1 Text en © The Author(s) 2017 This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Wang, Lei Ruan, Shigui Modeling Nosocomial Infections of Methicillin-Resistant Staphylococcus aureus with Environment Contamination(*) |
title | Modeling Nosocomial Infections of Methicillin-Resistant Staphylococcus aureus with Environment Contamination(*) |
title_full | Modeling Nosocomial Infections of Methicillin-Resistant Staphylococcus aureus with Environment Contamination(*) |
title_fullStr | Modeling Nosocomial Infections of Methicillin-Resistant Staphylococcus aureus with Environment Contamination(*) |
title_full_unstemmed | Modeling Nosocomial Infections of Methicillin-Resistant Staphylococcus aureus with Environment Contamination(*) |
title_short | Modeling Nosocomial Infections of Methicillin-Resistant Staphylococcus aureus with Environment Contamination(*) |
title_sort | modeling nosocomial infections of methicillin-resistant staphylococcus aureus with environment contamination(*) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5428062/ https://www.ncbi.nlm.nih.gov/pubmed/28373644 http://dx.doi.org/10.1038/s41598-017-00261-1 |
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